In the new “Internet age,” resources in the network (such as available services and information) can reside in many places. For instance, for server cloud computing applications, large number of data centers/servers collaborates to provide data storage/service/computational power to clients. The resource availability is dynamic due to the changing network condition, network activities, and applications. It is crucial to enable automatic management of these data centers/servers to respond quickly to and meet service requests workload, reliability, robustness, and performance requirements of clients. Moreover, services/information provided by servers/data centers is not homogeneous. Instead, there are rich and diverse. It can be very challenging to enable servers/data centers as well as clients to effectively manage such diverse information and track the dynamic information availability status. In a client cloud computing application where peer nodes collaborate together to both provide and consume service, there is the added complexity that client machines can be turned on and off in an unpredictable fashion. Hence, the resource management system must react fast enough to track the dynamic status of every node and update the rest of the network.
Various researches have been conducted in swarm based technology, in particular ant-based technology, has been used extensively to solve problems with distributed processing in networks. Existing network information/resource management systems propose to support information/resource distribution/retrieval in large-scale networks in a centralized and manual mode. Such systems require a server or a set of servers to manage network resource and the servers require consistent administrative effort to maintain their availability to clients. With ever growing size of the network, it becomes increasingly challenging to track and react to the dynamics of the network.
Researchers reported in both (1) Gianni Di Caro, Marco Dorigo, “Antnet: Distributed Stigmergetic Control for Communications Networks”, Journal of Artificial Intelligence Research 9 (1998), P 317-365, and (2) Ruud Schoonderwoerd, Owen Holland, Janet Bruten and Leon Rothkrantz, “Ant-based load balancing in telecommunication networks”, Adaptive Behavior, Vol 5, No 2, 1996, that the ant-based routing protocols are proven to generally support efficient routing in large-scale networks.
Currently, there is one swarm-based protocol described in: Tao Jiang and John S. Baras, “Ant-Based Adaptive Trust Evidence Distribution in MANET”, Proceedings of the 24th International Conference on Distributed Computing Systems Workshops (ICDCSW'04), 2004. This paper (herein “Jiang et al.”) provides ant-based information distribution. These authors use ant agents to retrieve certificates (as the trust evidence) from the mobile ad hoc networks (MANETs). Jiang et al. teach a system for directly searching for information that a node needs, rather than routing via a routing table. Instead the routing table is replaced with an information routing table using key words to look for specific information. The only information to be searched is a certificate, indexed by the target entity.